An implantable cardiac device is a medical device that is implanted in a patient to monitor electrical activity of the heart and to deliver appropriate electrical and/or drug therapy, as required. Implantable cardiac devices include, for example, pacemakers, cardioverters and defibrillators. The term “implantable cardioverter defibrillator” or simply “ICD” is used herein to refer to any implantable cardiac device. An ICD employs a battery to power its internal circuitry and to generate electrical therapy. The electrical therapy can include, for example, pacing pulses, cardioverting pulses and/or defibrillator pulses.
Heart failure is a growing medical challenge. In clinical practice today, most patients are managed effectively through pharmacological therapy such as beta-blockers, ACE inhibitors, and diuretics. If a patient's condition worsens, treatment may become more aggressive to include biventricular pacing and other implantable cardiac device therapy. Along with providing the primary objectives in the treatment of heart failure of improving symptoms, increasing the quality of life, and slowing disease progression, devices need to provide heart failure physicians with diagnostic parameters to monitor the patient's progress.
Currently, medical history and physical examination are the most important tools that a physician uses to determine and mark the progress of a heart failure patient. This involves much of the physician's time with the patient, as this may lead to the primary management program for the patient.
Included in most management programs is an exercise routine. It has been written extensively that adherence to exercise is a priority in improving or in maintaining good heath. Exercise diagnostics may help clinicians assess the compliance of the management programs prescribed to their patients, and possibly assist the patient in meeting those goals.
During exercise, the heart rate is a parameter or indicator of the amount of work that was required to provide blood and oxygen to the body. The maximum heart rate for a level of exercise corresponds to the conditioning of the heart. Other parameters, such as heart rate intensity, percent oxygen consumption (% VO2) reserve, metabolic equivalents (METS), and workload also provide data that is indicative of heart conditioning.
Heart rate recovery after exercise is evaluated as a clinical marker of good vagal activity and cardiac health. As the heart rate increases due to a reduction in vagal tone, the heart rate also decreases with a reactivation of vagal activity. A delayed response to the decreasing heart rate may be a good prognostic marker of overall mortality (Cole, C. et al., NEJM 341:18, 1351-1357 (1999)) and cardiac health. Cole suggests that a reduction of only 12 beats per minute after one minute from peak exercise has been shown to be an abnormal value.
As previously mentioned, adherence to an exercise routine is a priority in managing heart failure progression; therefore, it is critical that a physician monitor patient activity, i.e., the time the patient is moving around, and patient exercise, i.e., the time the patient is continuously moving around. One method of monitoring patient activity and exercise relies on subjective and often inaccurate reporting of exercise duration and workload/intensity level by the patient.
Other more objective methods rely on algorithms that monitor patient activity using physiological sensors. Such algorithms use a single, fixed activity-sensor exercise threshold to detect exercise duration. However, current sensors in use are one dimensional, in that they only detect patient movement in one direction, depending on there orientation with respect to the patient. For example, a sensor may be oriented such that it senses movement only in the horizontal, forward-backward direction. As a result, exercise formats involving vertically directed activity, such as climbing stairs or exercise such as biking cannot be easily detected. Additionally, each patient has different movement style—some may breathe hard enough to cause some sensor counts, and a single exercise threshold for all the patients may produce inaccurate results.
In order to help the physician objectively evaluate exercise compliance and heart failure progression using current sensor technology, a more reliable algorithm is desired. The algorithm should detect activity duration and exercise duration with enough accuracy so as not to include any daily activity such as office work, reading and talking, nor to overlook some types of exercise.